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Operations research

Project Leader(s): 

Postdoctoral fellow: Dr. Zhen Gao, Mechanical Engineering, University of Ontario Institute of Technology

Lead faculty member: Dr. Dan Zhang, Mechanical Engineering, University of Ontario Institute of Technology

This research develops a comprehensive methodology for the integrated optimization and control of human-friendly robotic technology that will be applied for the advanced healthcare and biomedical manipulation. Some original ideas, methods and algorithms are proposed in this research based on several novel mathematical models, which will benefit the development of general robotics in the direction of safety with high performance to human beings.

Project Leader(s): 

Dr. François Soumis, (École Polytechnique de Montréal)

Project team: 
Dr. Guy Desaulniers Guy, (École Polytechnique de Montréal)
Dr. Pierre Baptiste, (École Polytechnique de Montréal)
Dr. Jacques Desrosiers, (HEC Montréal)
Dr. Alain Hertz, (École Polytechnique de Montréal)
Dr. Sophie D’Amours, (Université Laval)
Funding period: 
April 1, 2021 - March 31, 2021
Project Leader(s): 

Dr. Anthony Vannelli, University of Guelph & Dr. Miguel F, AnjosEcole Polytechnique

Project team: 
Dr. Abdo Youssef Alfakih, University of Windsor
Dr. Kankar Bhattacharya, University of Waterloo
Dr. Claudio A. Canizares, University of Waterloo
Dr. Richard J. Caron, University of Windsor
Dr. Thomas Coleman, University of Waterloo
Dr. Tim N. Davidson, McMaster University
Dr. Antoine Deza, McMaster University
Dr. Samir Elhedhli, University of Waterloo
Dr. David Fuller, University of Waterloo
Dr. Elizabeth Jewkes, University of Waterloo
Dr. Paul McNicholas, University of Guelph
Dr. Chitra Rangan, University of Windsor
Dr. Tamás Terlaky, Lehigh University
Dr. Stephen Vavasis, University of Waterloo
Dr. Henry Wolkowicz, University of Waterloo
Dr. Guoqing Zhang, University of Windsor
Funding period: 
April 1, 2021 - March 31, 2021

Due to the explosive growth in the technology for manufacturing integrated circuits, modern chips contain millions of transistors. Using sophisticated optimization algorithms, it is possible to achieve notable increases in the performance of the chips, reduce the manufacturing costs, and produce faster, cheaper computing for society. Thus, the objective of this project is to enhance the solution of large-scale optimization problems arising in these applications.